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We propose a natural relaxation of differential privacy based on the Renyi divergence.
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C. Dwork, F. McSherry, K. Nissim, and A. D. Smith, “Calibrating noise to sensitivity in private data analysis,” in Third Theory of Cryptography Conference, TCC 2006 , S. Halevi and T. Rabin, Eds. Springer, 2006, pp. 265–284
2006
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C. Dwork, K. Kenthapadi, F. McSherry, I. Mironov, and M. Naor, “Our data, ourselves: Privacy via distributed noise generation,” in Advances in Cryptography—Eurocrypt ’06 . Springer, 2006, pp. 486–503
2006
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I. Mironov, O. Pandey, O. Reingold, and S. P. Vadhan, “Computational differential privacy,” in Advances in Cryptology—CRYPTO 2009 , S. Halevi, Ed., 2009, pp. 126–142
2009
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F. D. McSherry, “Privacy integrated queries: an extensible platform for privacy-preserving data analysis,” in Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data , C. Binnig and B. Dageville, Eds., 2009, pp. 19–30
2009
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Y. Mansour, M. Mohri, and A. Rostamizadeh, “Multiple source adaptation and the Rényi divergence,” in UAI ’09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence . AUAI Press, Jun. 2009, pp. 367–374
2009
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C. Dwork, G. N. Rothblum, and S. Vadhan, “Boosting and differential privacy,” in 51st Annual IEEE Symposium on Foundations of Computer Science (FOCS) , L. Trevisan, Ed. IEEE, Oct. 2010, pp. 51–60
2010
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A. McGregor, I. Mironov, T. Pitassi, O. Reingold, K. Talwar, and S. Vadhan, “The limits of two-party differential privacy,” in 51st Annual IEEE Symposium on Foundations of Computer Science (FOCS) , L. Trevisan, Ed. IEEE, 2010, pp. 81–90
2010
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A. Groce, J. Katz, and A. Yerukhimovich, “Limits of computational differential privacy in the client/server setting,” in Theory of Cryptography—8th Theory of Cryptography Conference, TCC 2011 , Y. Ishai, Ed., 2011, pp. 417–431
2011
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O. Shayevitz, “On Rényi measures and hypothesis testing,” in 2011 IEEE International Symposium on Information Theory Proceedings . IEEE, Jul. 2011, pp. 894–898
2011
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A. De, “Lower bounds in differential privacy,” in Theory of Cryptography—9th Theory of Cryptography Conference, TCC 2012 , R. Cramer, Ed., 2012, pp. 321–338
2012
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R. Bassily, A. Groce, J. Katz, and A. D. Smith, “Coupled-worlds privacy: Exploiting adversarial uncertainty in statistical data privacy,” in 54th Annual IEEE Symposium on Foundations of Computer Science , 2013, pp. 439–448
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A. Langlois, D. Stehlé, and R. Steinfeld, “GGHLite: More efficient multilinear maps from ideal lattices,” in Advances in Cryptology—EUROCRYPT 2014 , P. Q. Nguyen and E. Oswald, Eds. Springer Berlin Heidelberg, 2014, pp. 239–256
2014
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P. Kairouz, S. Oh, and P. Viswanath, “The composition theorem for differential privacy,” in Proceedings of the 32nd International Conference on Machine Learning (ICML) , 2015, pp. 1376–1385
2015
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J. Murtagh and S. Vadhan, “The complexity of computing the optimal composition of differential privacy,” in Theory of Cryptography—13th International Conference, TCC 2016-A, Part I , E. Kushilevitz and T. Malkin, Eds., 2016, pp. 157–175
2016
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C. Dwork and G. N. Rothblum, “Concentrated differential privacy,” CoRR , vol. abs/1603.01887, 2016
2016
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J. C. Duchi, M. I. Jordan, and M. J. Wainwright, “Local privacy and statistical minimax rates,” in 54th Annual IEEE Symposium on Foundations of Computer Science (FOCS) . IEEE, Oct. 2013, pp. 429–438
2013
Cited alongside, same era.
V. Lyubashevsky, C. Peikert, and O. Regev, “On ideal lattices and learning with errors over rings,” J. ACM , vol. 60, no. 6, pp. 43:1–43:35, Nov. 2013
2013
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D. Kifer and A. Machanavajjhala, “Pufferfish: A framework for mathematical privacy definitions,” ACM Transactions on Database Systems (TODS) , vol. 39, no. 1, pp. 3:1–3:36, Jan. 2014
2014
Cited alongside, same era.
2014
Cited alongside, same era.
M. Bun and T. Steinke, “Concentrated differential privacy: Simplifications, extensions, and lower bounds,” in Theory of Cryptography—14th International Conference, TCC 2016-B, Part I , M. Hirt and A. D. Smith, Eds., 2016, pp. 635–658
2016
Later among the works it cites.
M. Abadi, A. Chu, I. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, and L. Zhang, “Deep learning with differential privacy,” in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS) . ACM, 2016, pp. 308–318
2016
Later among the works it cites.
M. Bun, Y. Chen, and S. P. Vadhan, “Separating computational and statistical differential privacy in the client-server model,” in Theory of Cryptography—14th International Conference, TCC 2016-B, Part I , M. Hirt and A. D. Smith, Eds., 2016, pp. 607–634
2016
Later among the works it cites.
F. D. McSherry, “How many secrets do you have?” https://github.com/frankmcsherry/blog/blob/master/posts/2017-02-08.md
2017
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